Welcome to the IMAP (“Integrated Microbiome Analysis Pipelines”) framework—a meticulously crafted structure empowering researchers, scientists, developers, and enthusiasts in conducting thorough analyses of intricate microbiome data. Each chapter within IMAP stands as an independent GitHub repository (repo), offering a dedicated space for focused exploration and understanding.
GitHub Repo: URL: https://github.com/tmbuza/imap-project-overview/
GitHub Pages: URL: https://tmbuza.github.io/imap-project-overview/
Our primary objectives revolve around reproducibility, clarity, and efficiency. We understand the challenges inherent in microbiome data analysis and aim to equip you with the tools and strategies necessary to navigate this complex landscape with confidence.
Microbiome data analysis encompasses a diverse set of tools and platforms, from R and Python for statistical analysis to Snakemake for workflow management, and GitHub Actions for continuous integration and deployment. To streamline this process and ensure reproducibility, we adopt a strategy of managing these tools within unified environments.
RStudio for R Analysis: Discover how we leverage RStudio for developing and documenting R scripts or notebooks. All required R packages are installed and managed within the R environment, providing a controlled and reproducible setup.
Jupyter Notebook for Python Analysis: Dive into the use of Jupyter Notebooks for Python-based analysis. Python packages are isolated within the Jupyter environment, ensuring a clean and consistent setup.
Conda Environment for Snakemake Workflows: Explore the versatility of Snakemake workflows, managed within a dedicated Conda environment. This approach guarantees that dependencies for each workflow are isolated and reproducible.
GitHub Actions for Continuous Integration and Deployment: Learn how we utilize GitHub Actions to automate continuous integration and deployment processes. This ensures the consistent and automated testing, building, and deployment of our microbiome data analysis workflows, contributing to a more efficient and reliable development pipeline.
Outputs from RStudio, Jupyter Notebook, and Snakemake workflows converge in a final HTML report, serving as the culmination of our analytical efforts.
Comprehensive Insights: The final HTML report offers a holistic view of the microbiome analysis, incorporating both the code and results from various components.
Efficient Collaboration: Discover how consolidating outputs enhances collaboration, enabling team members to easily reproduce and build upon the analysis.
A pivotal aspect of our methodology involves the utilization of Snakemake rule graphs, serving as invaluable tools to enhance transparency in our computational analyses. These graphical representations provide a lucid and intuitive portrayal of the logical sequence of tasks, contributing to a heightened understanding for users, readers, collaborators, or reviewers.
We encourage readers to make use of the Snakemake rule graphs featured in the appendix section of IMAP chapters dedicated to intensive computational analyses. These visual aids stand as comprehensive resources, aiding in the navigation and comprehension of the intricate structure and dependencies embedded within each analysis.